Description Usage Arguments Details Value Examples
pipeLIMMA
Run a pipeline of LIMMA functions for differential gene expression.
1 2 3 4 |
counts |
A count matrix |
info |
An experimental design matrix |
formula |
A character string that can be coerced to a formula. Specify if a contrast model is not desired. |
contrast.matrix |
A matrix of contrasts, usually created by a call from limma:makeContrasts. Used only when limma:contrast.fit is intended as the statistical modeling function. NULL values force a traditional test of effects via limma::lmFit/ebayes. |
block |
A string that represents an individual that was repeatedly measured, if NULL, runs the analysis without a blocking / duplicate correlation factor |
design |
A design matrix, usually created by a call from "model.matrix". Used only if limma:contrast.fit is intended as the statistical modeling function. NULL values force a traditional test of effects via limma::lmFit/ebayes. |
runVoom |
Logical, if TRUE, normalizes the counts matrix via voom. If FALSE, assumes the counts matrix is already voom-normalized. Pre-running voom will speed up analyses with multiple pipeLIMMA calls. |
use.qualityWeights |
Logical, run voom with quality weights or not? |
use.topTable |
Logical, report F-statistics across all factors? If true, a third element is returned called fstats. |
geneIDs |
The names of genes. If NA, use row names from counts matrix |
verbose |
Logical, return progress updates? |
plotVoom |
Logical, plot the voom fit? Defaults to FALSE |
... |
additional arguments, not currently in use. |
This function runs the following pipeline:
1. calculate normalization factors via edgeR::calcNormFactors
2. Run limma::voom transformation
3. Run limma:lmFit linear modeling
4. Run limma::ebayes statistical modeling
5. Collect Log2 Fold-Changes using limma:topTable
6. Collate and ouput statistics and voom transformed data
a list with 2 elements (if simple=TRUE)
"stats": the statsistics generated from ebayes and topTable
"voom": the voom normalized counts data
"fstats": if a formula is provided, the toptable returned fstatsistics across all estimates of each factor
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ## Not run:
data(kidney) # from simseq
counts<-kidney$counts
counts<-counts[sample(1:nrow(counts),1000),]
info<-data.frame(rep=kidney$replic,
treatment=kidney$treatment)
stats<-pipeLIMMA(counts=counts,
info=info,
formula = " ~ treatment",
block=info$rep)
stats<-pipeLIMMA(counts=counts,
info=info,
formula = " ~ treatment",
block=NULL)
## End(Not run)
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